Definition and forecasting of GGDP in the landscape of climate issues

Abstract

In this paper, we propose a GGDP assessment system for climate mitigation, analyze its ecological impacts, and discuss the potential advantages and disadvantages of the GDP transformation. Firstly, the definition and traditional calculation of GGDP are elaborated, and eight indicators are divided into direct and indirect factors for climate mitigation. Then, five rep-presentative countries are selected and the data of indicators are substituted. Besides, the weights corresponding to the indicators are calculated by the entropy weighting method and the coefficient of variation method respectively. Next, the comprehensive weighting coefficients of the indicators are figured out by the combined method. The established GGDP system based on the CV-EWM evaluation model is used to obtain the GDP and GGDP change of five countries from 2001 to 2022. Additionally, the BP neural network algorithm is used to predict the trends of CO2 and temperature under the two systems of GDP and GGDP, respectively. Finally, the neural network was optimized by a genetic algorithm to establish the global climate impact assessment model based on GA-BP neural network prediction, and the global effect of the GGDP system on climate mitigation issues was studied.